This also suggests that, if you are hiring for employee number 9 for a role where you already have 8 others, just hire the first one that you come across that is similar to those you already have.
In this case, you use the previous 8 as calibration set and you go straight to hiring for number 9.
If you adhere strictly to the rule and hire “the next best”, you will, in time, also raise the level of the whole team, avoiding the natural downward drift of hiring “similar, good enough candidates” instead.
That's a different case, as you already have the benchmark rather than starting with no context for the pool. So, it's less the secretary problem and more a fixed-bar-you-hire-above :)
I like the perspective of setting the bar at your best team member and hiring above it. Thanks for your perspective, Luca!
Actually it’s the same secretary situation, only you see it as such if you zoom out in time.
The big idea here is “when you need to choose among candidates, use the first 37% as calibration set and then hire the next best”, with the numerical indication being the differentiating factor against common sense.
If you are hiring for a position for which you have hired before, and as long as the requirements have not changed, the previous candidates already count towards the 37%.
Going even bigger in the application: when you need to choose among things, estimate the size of the candidate pool, pick 37% at random to calibrate and go through the rest as prescribed.
Or, extending the idea even more: “37% is the proportion of things you need to evaluate before being reasonably sure that you know what good looks like”.
There are plenty of perspectives to look at it, that is for sure, Luca.
For me, the key insight is to remember the calibration phase. I like the idea that 37% is the proportion of options you should review before being reasonably sure that you know what good looks like.
Interesting.
This also suggests that, if you are hiring for employee number 9 for a role where you already have 8 others, just hire the first one that you come across that is similar to those you already have.
In this case, you use the previous 8 as calibration set and you go straight to hiring for number 9.
If you adhere strictly to the rule and hire “the next best”, you will, in time, also raise the level of the whole team, avoiding the natural downward drift of hiring “similar, good enough candidates” instead.
That's a different case, as you already have the benchmark rather than starting with no context for the pool. So, it's less the secretary problem and more a fixed-bar-you-hire-above :)
I like the perspective of setting the bar at your best team member and hiring above it. Thanks for your perspective, Luca!
Actually it’s the same secretary situation, only you see it as such if you zoom out in time.
The big idea here is “when you need to choose among candidates, use the first 37% as calibration set and then hire the next best”, with the numerical indication being the differentiating factor against common sense.
If you are hiring for a position for which you have hired before, and as long as the requirements have not changed, the previous candidates already count towards the 37%.
Going even bigger in the application: when you need to choose among things, estimate the size of the candidate pool, pick 37% at random to calibrate and go through the rest as prescribed.
Or, extending the idea even more: “37% is the proportion of things you need to evaluate before being reasonably sure that you know what good looks like”.
Damn, this got me going!
Thoughts?
There are plenty of perspectives to look at it, that is for sure, Luca.
For me, the key insight is to remember the calibration phase. I like the idea that 37% is the proportion of options you should review before being reasonably sure that you know what good looks like.